flankr individual CAFs

individual_CAFs.R

library(tidyverse)
library(flankr)

# get example data from flankr
# ONLY SHOWING FOR CONGRUENT DATA.
d <- flankr::exampleData %>% 
  filter(congruency == "congruent")

# how many subjects?
n_subjects <- length(unique(d$subject))


# initiate caf tibble
caf_data <- tibble(
  id = 1:n_subjects, 
  rt_1 = 0, 
  rt_2 = 0, 
  rt_3 = 0, 
  rt_4 = 0, 
  acc_1 = 0,
  acc_2 = 0, 
  acc_3 = 0, 
  acc_4 = 0
)

# loop over subjects
for(i in 1:n_subjects){
  
  # get the current subject's data
  sub_data <- d %>% 
    filter(subject == i)
  
  # get their CAFs
  sub_caf <- flankr::caf(sub_data, multipleSubjects = FALSE)
  
  # store the data
  caf_data[i, 2] <- sub_caf[1, 1]
  caf_data[i, 3] <- sub_caf[1, 2]
  caf_data[i, 4] <- sub_caf[1, 3]
  caf_data[i, 5] <- sub_caf[1, 4]
  caf_data[i, 6] <- sub_caf[2, 1]
  caf_data[i, 7] <- sub_caf[2, 2]
  caf_data[i, 8] <- sub_caf[2, 3]
  caf_data[i, 9] <- sub_caf[2, 4]
  
}

# THEN REPEAT FOR INCOGNRUENT. OR, BE MORE FANCY WITH HOW THE ABOVE
# IS HANDLED!